Влияние инфляции на взаимосвязь стабилизации и роста экономики некоторых стран Восточной Европы и бывшего СССР

In many countries, particularly in sub-Saharan Africa, Demographic and Health Surveys (DHSs) are the main way of estimating HIV prevalence nationally in the general population. Some DHSs record the longitude and latitude of the survey clusters.We present three methodological approaches for mapping spatial variations in HIV prevalence using the DHSs. These approaches are applied to simulated DHS samplings from a model country. The estimated surfaces are then compared with the model’s initial surface.We demonstrate that a method using kernel estimators with adaptive bandwidths size of equal number of persons observed can be used to estimate the main regional trends in epidemics. Application to Burkina Faso’s 2003 DHS data provides a plausible image of that country’s epidemiological situation

HIV-1 disease progression in immune-competent HIV-1-infected and breastfeeding mothers participating in the ANRS 12174 clinical trial in Burkina Faso, South Africa, Uganda and Zambia: a cohort study

International audienceObjective We have assessed HIV-1 disease progression among HIV-1-positive mothers in relation to duration of any or exclusive breast feeding in the context of ANRS 12174 trial.Methods The analysis was completed on 203, 212, 272 and 529 HIV-1-positive and lactating mothers with CD4 count >350 cells/µL from Burkina Faso, South Africa, Uganda and Zambia, respectively. The trial compared lamivudine and lopinavir/ritonavir as a peri-exposure prophylaxis during a 50-week follow-up time. A multiple logistic regression model was run with the mothers’ weight, CD4 count and HIV-1 viral load as separate dependent variables, then combined into a dependent composite endpoint called HIV-1 disease progression where HIV-1 viral load was replaced by the HIV-1 clinical stage. Exclusive or predominant breast feeding (EPBF) and any breastfeeding duration were the key explanatory variables.Results In the adjusted model, the associations between EPBF duration and weight change, CD4 cell count and the HIV-1 viral load were consistently insignificant. The CD4 cell count was associated with a significantly higher mothers’ body mass index (BMI; a mean increase of 4.9 (95% CI 2.1 to 7.7) CD4 cells/µL per each additional kilogram per square metre of BMI) and haemoglobin concentration (19.4 (95% CI 11.4 to 27.4) CD4 cells/µL per each additional gram per decilitre of haemoglobin concentration). There was no significant association between EPBF duration and HIV-1 disease progression. A higher education level was a factor associated with a slower HIV-1 disease progression.Conclusion Breast feeding was not a risk factor for a faster progression of HIV-1 disease in mothers of this cohort with a baseline CD4 cell count >350 cells/µL

Changes in body mass index and hemoglobin concentration in breastfeeding women living with HIV with a CD4 count over 350: Results from 4 African countries (The ANRS 12174 trial).

INTRODUCTION: Breastfeeding is recommended for infants born to HIV-infected women in low-income settings. Both breastfeeding and HIV-infection are energy demanding. Our objective was to explore how exclusive and predominant breastfeeding changes body mass index (BMI) among breastfeeding HIV1-positive women participating in the ANRS12174 trial (clinical trial no NCT0064026). METHODS: HIV-positive women (n = 1 267) with CD4 count >350, intending to breastfeed HIV-negative infants were enrolled from Burkina Faso, South Africa, Uganda and Zambia and counselled on breastfeeding. N = 1 216 were included in the analysis. The trial compared Lamivudine and Lopinavir/Ritonavir as a peri-exposure prophylaxis. We ran a linear mixed-effect model with BMI as the dependent variable and exclusive or predominant breastfeeding duration as the key explanatory variable. RESULTS: Any breastfeeding or exclusive/predominant) breastfeeding was initiated by 99.6% and 98.6% of the mothers respectively in the first week after birth. The median (interquartile range: IQR) duration of the group that did any breastfeeding or the group that did exclusive /predominant breastfeeding were 9.5 (7.5; 10.6) and 5.8 (5.6; 5.9)) months, respectively. The median (IQR) age, BMI, CD4 count, and HIV viral load at baseline (day 7) were 27 (23.3; 31) years, 23.7 (21.3; 27.0) kg/m2, 530 (432.5; 668.5) cells/μl and 0.1 (0.8; 13.7)1000 copies/mL, respectively. No major change in mean BMI was seen in this cohort over a 50-week period during lactation. The mean change between 26 and 50 weeks after birth was 0.7 kg/m2. Baseline mean BMI (measured on day 7 postpartum) and CD4 count were positively associated with maternal BMI change, with a mean increase of 1.0 kg/m2 (0.9; 1.0) per each additional baseline-BMI kilogram and 0.3 kg/m2 (0.2; 0.5) for each additional CD4 cell/μl, respectively. CONCLUSION: Breastfeeding was not negatively correlated with the BMI of HIV-1 infected Sub-Saharan African mothers. However, a higher baseline BMI and a CD4 count >500 cells/μl were associated with maternal BMI during the exclusive/ predominant breastfeeding period. Considering the benefits of breast milk for the infants and the recurrent results from different studies that breastfeeding is not harmful to the HIV-1-infected mothers, this study also supports the WHO 2016 guidelines on infant feeding that mothers living with HIV should breastfeed where formula is not safe for at least 12 months and up to 24 months, given that the right treatment or prophylaxis for the infection is administered. These findings and conclusions cannot be extrapolated to women who are immune-compromised or have AIDS

Mitochondrial DNA parameters in blood of infants receiving lopinavir/ritonavir or lamivudine prophylaxis to prevent breastfeeding transmission of HIV-1

Children who are human immunodeficiency virus (HIV)-exposed but uninfected (CHEU) accumulate maternal HIV and antiretroviral exposures through pregnancy, postnatal prophylaxis, and breastfeeding. Here, we compared the dynamics of mitochondrial DNA (mtDNA) parameters in African breastfed CHEU receiving lopinavir/ritonavir (LPV/r) or lamivudine (3TC) pre-exposure prophylaxis during the first year of life. The number of mtDNA copies per cell (MCN) and the proportion of deleted mtDNA (MDD) were assessed at day 7 and at week 50 post-delivery (PrEP group). mtDNA depletion was defined as a 50% or more decrease from the initial value, and mtDNA deletions was the detection of mtDNA molecules with large DNA fragment loss. We also performed a sub-analysis with CHEU who did not receive a prophylactic treatment in South Africa (control group). From day seven to week 50, MCN decreased with a median of 41.7% (interquartile range, IQR: 12.1; 64.4) in the PrEP group. The proportion of children with mtDNA depletion was not significantly different between the two prophylactic regimens. Poisson regressions showed that LPV/r and 3TC were associated with mtDNA depletion (reference: control group; LPV/r: PR = 1.75 (CI95%: 1.15–2.68), p < 0.01; 3TC: PR = 1.54 (CI95%: 1.00–2.37), p = 0.05). Moreover, the proportion of children with MDD was unexpectedly high before randomisation in both groups. Long-term health impacts of these mitochondrial DNA parameters should be investigated further for both CHEU and HIV-infected children receiving LPV/r- or 3TC- based regimens.http://www.mdpi.com/journal/jcmpm2021Paediatrics and Child Healt

Méthodes pour cartographier les tendances régionales de la prévalence du VIH à partir des Enquêtes Démographiques et de Santé (EDS)

Pour de nombreux pays, en particulier en Afrique subsaharienne, les Enquêtes Démographiques et de Santé (EDS) constituent la principale estimation de la prévalence du VIH au niveau national et en population générale. Plusieurs EDS collectent la longitude et la latitude des grappes enquêtées.Dans cet article, nous présentons trois approches méthodologiques pour cartographier les variations spatiales de la prévalence du VIH à partir des EDS. Ces approches sont appliquées à des simulations d’EDS échantillonnées à partir d’un pays modèle. Les surfaces estimées sont alors comparées à la surface initiale du modèle.Nous montrons qu’une méthode utilisant des estimateurs à noyau à fenêtres adaptatives de même effectif permet d’estimer les principales tendances régionales des épidémies. Son application aux données de l’EDS 2003 du Burkina Faso fournit une image plausible de la situation épidémiologique dans ce pays.For many countries, in particular in sub-Saharan Africa, Demographic and Health Surveys (DHS) are the main estimates of HIV prevalence at national levels in general population. Several DHS collect longitude and latitude of surveyed clusters.In this paper, we present three methodological approaches for mapping spatial variations of HIV prevalence from DHS. These approaches are applied to DHS simulation sampled from a model country. The estimated surfaces are then compared with the initial surface of the model.We show that a method using kernel estimators with adaptive bandwidths of the same number of observed people allows estimating main regional trends of the epidemics. Its application to data from 2003 DHS of Burkina Faso give a plausible picture of the epidemiological situation in this country

Methods for mapping regional trends of HIV prevalence from Demographic and Health Surveys (DHS)

For many countries, in particular in sub-Saharan Africa, Demographic and Health Surveys (DHS) are the main estimates of HIV prevalence at national levels in general population. Several DHS collect longitude and latitude of surveyed clusters.In this paper, we present three methodological approaches for mapping spatial variations of HIV prevalence from DHS. These approaches are applied to DHS simulation sampled from a model country. The estimated surfaces are then compared with the initial surface of the model.We show that a method using kernel estimators with adaptive bandwidths of the same number of observed people allows estimating main regional trends of the epidemics. Its application to data from 2003 DHS of Burkina Faso give a plausible picture of the epidemiological situation in this country. Keywords: interpolation, regional trends, methodology, demographic and health surveys, developing countries, HI

Comparaisons locales de la surveillance sentinelle des femmes enceintes et des Enquêtes Démographiques et de Santé au Burkina Faso et au Cameroun

International audienceObjectifLes prévalences nationales du VIH ont été historiquement estimées à partir de la surveillance sentinelle en cliniques prénatales (CPN). Depuis 2001, les Enquêtes Démographiques et de Santé (EDS) en population générale constituent une nouvelle source d’informations. Pour plusieurs pays, les estimations entre ces deux sources divergent, principalement en raison de la localisation des sites sentinelles retenus. Certains travaux ont montré que les CPN pouvaient constituer un bon indicateur local. Nous cherchons ici à comparer localement EDS et CPN afin de préciser la représentativité de ces dernières.MéthodeNous avons eu recours à des techniques d’analyse en composantes d’échelle et d’interpolation spatiale afin de cartographier les variations infrarégionales de la prévalence du VIH à partir des EDS. La méthode employée a été testée à partir d’une modélisation avant d’être appliquée aux EDS 2003 du Burkina Faso et 2004 du Cameroun. Un programme informatique a été spécialement conçu à cette fin (http://www.ceped.org/prevR). Nous obtenons les tendances régionales de la prévalence du VIH dans un rayon de 30 à 90 kilomètres, que nous comparons avec les données CPN.RésultatsLa prévalence du VIH mesurée en CPN est fortement dépendante de la zone de recrutement (ZR) de cette dernière. Pour les petites agglomérations isolées, le nombre limité de cliniques induit que leur ZR correspond approximativement à l’agglomération et son voisinage plus ou moins proche. Dans les grandes villes ou les régions fortement urbanisées, la diversité des CPN disponibles rendent les ZR plus complexes. Elles peuvent s’interpénétrer et/ou se superposer. Les CPN ne seront pas forcément représentatives de l’agglomération étudiée. Les CPN situées en milieu rurale traduisent pour leur part une prévalence très localisée qui peut diverger de la tendance régionale.ConclusionLa surveillance sentinelle en CPN peut s’avérer un mauvais indicateur des niveaux régionaux de l’épidémie, en fonction de leurs zones de recrutement et des variations spatiales de la prévalence. Une comparaison avec d’autres sources est donc nécessaire avant de pouvoir généraliser une observation réalisée en CPN. Cependant, elle reste adaptée pour une surveillance locale des tendances temporelles de l’épidémie

Cartographier les données des Enquêtes Démographiques et de Santé à partir des coordonnées des zones d'enquête

International audienceLes enquêtes démographiques et de santé (EDS) constituent une source de données standardisées bien connues des démographes. Nombre d’entre elles incorporent depuis longtemps les coordonnées longitude/latitude des zones enquêtées (grappes). Cependant, peu de travaux cartographiques exploitent cette information, principalement en raison d’un problème méthodologique. En effet, le nombre de personnes enquêtées dans une grappe est le plus souvent trop réduit (moins de 40) pour calculer des indicateurs statistiquement significatifs par grappe. D’autre part, les méthodes d’interpolation spatiale classique présupposent une mesure relativement précise du phénomène étudié en chaque point. Notre approche consiste donc à estimer la prévalence d’un phénomène en chaque grappe, à partir des grappes voisines, en ayant recours à des cercles de même effectif, puis à interpoler ces prévalences estimées par krigeage. Il est possible par ailleurs de prendre en compte le milieu de résidence après recodification. Outre l’application de cette approche à la prévalence du VIH du Burkina Faso et du Cameroun, nous présentons les résultats obtenus par simulation d’EDS sur un pays modèle

Mapping HIV prevalence in Africa for a better understanding of epidemics : example from Burkina Faso using 2003 demographic and health survey data

BackgroundsSince 2001, several Demographic and Health Surveys (DHS) include HIV testing. We developed a generic approach to map spatial trends of HIV prevalence from DHS (free software online). We present how our results from Burkina Faso 2003 DHS shed new light on HIV epidemics.MethodsAn estimation is made of regional spatial trends of HIV prevalence for each surveyed cluster by aggregating data from neighbouring clusters, using rings of the same number of tested persons and taking into account main urban agglomerations. The map is then generated by spatial interpolation.ResultsJPEG - 178.2 kioThis map is coherent with the knowledge we had of HIV epidemic in this country. Prevalence is higher in main cities and small cities along main roads.The region around Diébougou and Gaoua was particularly affected, a data which had not shown on antenatal surveillance. In addition to its proximity to Ivory Coast and Ghana, it is a major gold-washing zone which also has lot of migrant men and sex workers.The map showed similarities with migration areas in the 80’s and 90’s and with repatriate returns from Ivory Coast at the end of 2002 and beginning of 2003.Lastly, our results diverge from antenatal surveillance around Kaya. The high prevalence observed in this rural clinic is not representative of the low prevalence at a regional level.ConclusionHIV prevalence mapping highlights differences that were not visible using antenatal surveillance ; allows identifying most prevalent areas ; constitutes a monitoring and evaluation tool ; and suggest new research fields to investigate

Estimating effect of non response on HIV prevalence estimates from Demographic and Health Surveys

AimIn most countries in Sub-Saharan Africa, Demographic and Health Surveys (DHS) with HIV testing became the only measure of HIV prevalence in general population. Significant non response rate were often cited to explain differences between DHS results and estimations from sentinel surveillance in antenatal clinics. The objective of this presentation consists to predict with multivariate models the prevalence of non tested persons in order to estimate the effect of non response on national estimates.Method / IssueWe used data from 9 DHS surveys (Burkina Faso 2003, Cameroon 2004, Ethiopia 2005, Ghana 2003, Kenya 2003, Lesotho 2004, Malawi 2004, Senegal 2005 and Tanzanie 2003) where HIV results could be linked with data from household and individual questionnaires. Logistic regression were calculated for each country, separately for men and women 15-49 years old, with common predictor variables : region, place of residence, age group, education, wealth index, marital status, work status, having radio or television, age at first sexual intercourse, recent sexual activities, using condom at last sexual intercourse, number of partners in last 12 months, smoking, STI in last 12 months, female and male circumcision and willing to care for relative with AIDS. For each group, adjusted prevalence was calculated by using observed prevalence for tested people and estimated prevalence for non tested people.Results / CommentsThe non response rates in these 9 studies vary from 7.9% to 34.2%. Estimated prevalence of non tested persons is usually higher than observed prevalence of tested persons : in 15 groups on 18, the ratio exceeds 1 (it vary from 0.820 to 2.424). Nevertheless, ratios of adjusted prevalence to observed prevalence remain relatively small (from 0.956 to 1.251). Except for men in Lesotho and women in Malawi, differences between adjusted and observed prevalence is less than 0.5 points. In both cases, number of tested persons was small (less than 3’000). No relation was found between non response rate and ratio of non tested to tested or ratio of adjusted prevalence to observed prevalence. Nevertheless, highest ratio of adjusted prevalence to observed prevalence were found for groups with smallest prevalence (<3%). But this effect is probably a consequence of a small statistical power.DiscussionIf differences between adjusted and observed prevalence are more important than in a precedent survey conducted by Mishra et al. in 2006 on 5 DHS, the overall effect of non response bias on national HIV estimates tend to be small. Adjustments need to be interpreted with caution due to the limited information available to predict the prevalence of non tested people, in particular for people who did not answer the individual questionnaire and for whom only household questionnaire data were used